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An approximate algorithm for the two-dimensional air cargo revenue management problem

Author

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  • Huang, Kuancheng
  • Chang, Ko-chen

Abstract

For the air cargo revenue management problem, this study developed a solution algorithm based on approximating the expected revenue function in the dynamic programming (DP) model while taking into account the stochastic volume and weight of shipments. In order to alleviate the computational load, the approximation was achieved by computing only a limited number of points in the DP state space. In the simulation experiment, the developed algorithm was compared with a recent heuristic algorithm based on de-coupling the relationship between weight and volume. It was found that the approach of this study can generate higher revenue than the de-coupling control for most of the cases.

Suggested Citation

  • Huang, Kuancheng & Chang, Ko-chen, 2010. "An approximate algorithm for the two-dimensional air cargo revenue management problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(3), pages 426-435, May.
    • Handle: RePEc:eee:transe:v:46:y:2010:i:3:p:426-435
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    Citations

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    Cited by:

    1. Moussawi-Haidar, Lama & Nasr, Walid & Jalloul, Maya, 2021. "Standardized cargo network revenue management with dual channels under stochastic and time-dependent demand," European Journal of Operational Research, Elsevier, vol. 295(1), pages 275-291.
    2. Wang, Xinchang, 2017. "Static and dynamic resource allocation models for single-leg transportation markets with service disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 87-108.
    3. Wang, Xinchang, 2016. "Stochastic resource allocation for containerized cargo transportation networks when capacities are uncertain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 334-357.
    4. Masato Wada & Felipe Delgado & Bernardo K. Pagnoncelli, 2017. "A risk averse approach to the capacity allocation problem in the airline cargo industry," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(6), pages 643-651, June.
    5. Wang, Shuaian & Wang, Hua & Meng, Qiang, 2015. "Itinerary provision and pricing in container liner shipping revenue management," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 135-146.
    6. Yu, Shunan & Yang, Zhongzhen & Zhang, Wei, 2019. "Differential pricing strategies of air freight transport carriers in the spot market," Journal of Air Transport Management, Elsevier, vol. 75(C), pages 9-15.
    7. Ching-Cheng Chao & Taih-Cherng Lirn & Kuo-Chung Shang, 2013. "Market segmentation of airline cargo transport," The Service Industries Journal, Taylor & Francis Journals, vol. 33(15-16), pages 1672-1685, December.
    8. Wang, Tingsong & Meng, Qiang & Wang, Shuaian & Qu, Xiaobo, 2021. "A two-stage stochastic nonlinear integer-programming model for slot allocation of a liner container shipping service," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 143-160.
    9. Feng, Bo & Li, Yanzhi & Shen, Huaxiao, 2015. "Tying mechanism for airlines’ air cargo capacity allocation," European Journal of Operational Research, Elsevier, vol. 244(1), pages 322-330.
    10. Klein, Robert & Koch, Sebastian & Steinhardt, Claudius & Strauss, Arne K., 2020. "A review of revenue management: Recent generalizations and advances in industry applications," European Journal of Operational Research, Elsevier, vol. 284(2), pages 397-412.
    11. Chao, Ching-Cheng & Li, Ru-Guo, 2017. "Effects of cargo types and load efficiency on airline cargo revenues," Journal of Air Transport Management, Elsevier, vol. 61(C), pages 26-33.
    12. Bin Qiao & Shenle Pan & Eric Ballot, 2016. "Less-than-truckload Dynamic Pricing Model in Physical Internet," Post-Print hal-01326416, HAL.
    13. Ankersmit, Steven & Rezaei, Jafar & Tavasszy, Lori, 2014. "The potential of horizontal collaboration in airport ground freight services," Journal of Air Transport Management, Elsevier, vol. 40(C), pages 169-181.
    14. Wu, You & Lange, Anne & Mantin, Benny, 2022. "Who benefits from air service agreements? The case of international air cargo operations," Transportation Research Part B: Methodological, Elsevier, vol. 163(C), pages 281-303.
    15. Moussawi-Haidar, Lama, 2014. "Optimal solution for a cargo revenue management problem with allotment and spot arrivals," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 72(C), pages 173-191.
    16. Bin Qiao & Shenle Pan & Eric Ballot, 2019. "Dynamic pricing model for less-than-truckload carriers in the Physical Internet," Journal of Intelligent Manufacturing, Springer, vol. 30(7), pages 2631-2643, October.

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